1. Field of the Invention
This invention relates generally to optically-based target detection.
2. Description of the Related Art
Target detection is the task of determining the presence or absence of a known object, referred to as the target. An action may then be taken based on the presence/absence of the target. This is useful in a variety of applications, including factory automation, automobiles, and consumer electronics. For example, a smart automobile could use pedestrian detection to avoid accidents. In another application, a smart quality-check system may reject defective products in an assembly line to improve production quality.
The conventional approach for performing target detection involves acquiring images with a camera and then processing the acquired images to determine if the target is present. Unfortunately, camera sensor arrays and software/hardware based image processing solutions have significant power requirements, which render them unsuitable for target detection and monitoring in low-power applications. Furthermore, in high-speed applications such as semiconductor wafer inspection, the speed of camera based target detectors is constrained by the need to acquire, transmit and process large amounts of image data.
As a specific example, quick recognition (QR) codes are popular two-dimensional barcodes used to encode text, URLs, vCards, and other forms of data. Although originally developed for tracking parts in factories, QR codes have found renewed interest in mobile tagging after the rapid emergence of smart camera phones and cameras on other types of mobile compute devices. Notably, the use of QR codes allows high speed reading of their encoded content with reduced read-out errors. However, QR codes are traditionally detected by acquiring their images using a conventional imaging system, a sensor array with a large number of pixels, and image-processing algorithms. If a mobile compute device is tasked with continuously monitoring whether a QR code is present in its field of view, then it must be constantly acquiring images and processing them to detect the presence of QR codes. This is a significant power drain.
Thus, there is a need for improved approaches to target detection.